• Asian Pacific Journal of Cancer Prevention
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• v.17 no.12
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• pp.5287-5294
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• 2016

Background: Breast cancer is a worldwide public health concern and is the most prevalent type of cancer in women in the United States. This study concerned the best fit of statistical probability models on the basis of survival times for nine state cancer registries: California, Connecticut, Georgia, Hawaii, Iowa, Michigan, New Mexico, Utah, and Washington. Materials and Methods: A probability random sampling method was applied to select and extract records of 2,000 breast cancer patients from the Surveillance Epidemiology and End Results (SEER) database for each of the nine state cancer registries used in this study. EasyFit software was utilized to identify the best probability models by using goodness of fit tests, and to estimate parameters for various statistical probability distributions that fit survival data. Results: Statistical analysis for the summary of statistics is reported for each of the states for the years 1973 to 2012. Kolmogorov-Smirnov, Anderson-Darling, and Chi-squared goodness of fit test values were used for survival data, the highest values of goodness of fit statistics being considered indicative of the best fit survival model for each state. Conclusions: It was found that California, Connecticut, Georgia, Iowa, New Mexico, and Washington followed the Burr probability distribution, while the Dagum probability distribution gave the best fit for Michigan and Utah, and Hawaii followed the Gamma probability distribution. These findings highlight differences between states through selected sociodemographic variables and also demonstrate probability modeling differences in breast cancer survival times. The results of this study can be used to guide healthcare providers and researchers for further investigations into social and environmental factors in order to reduce the occurrence of and mortality due to breast cancer.

• The KIPS Transactions:PartD
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• v.10D no.2
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• pp.233-246
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• 2003

The mediator-based system integrates heterogeneous information systems with the flexible manner. But it does not give much attention on the query optimization issues, especially for the query reusing. The other thing is that it does not use standardized metadata for schema matching. To improve this two issues, we propose mediator-based Distributed Information Integration System (DIIS) which uses query caching regarding performance and uses ISO/IEC 11179 metadata registry in terms of standardization. The DIIS is designed to provide decision-making support, which logically integrates the distributed heterogeneous business information systems based on the Web environment. We designed the system in the aspect of three-layer expression formula architecture using the layered pattern to improve the system reusability and to facilitate the system maintenance. The functionality and flow of core components of three-layer architecture are expressed in terms of process line diagrams and assembly line diagrams of Eriksson Penker Extension Model (EPEM), a methodology of an extension of UML. For the implementation, Supply Chain Management (SCM) domain is used. And we used the Web-based environment for user interface. The DIIS supports functions of query caching and query reusability through Query Function Manager (QFM) and Query Function Repository (QFR) such that it enhances the query processing speed and query reusability by caching the frequently used queries and optimizing the query cost. The DIIS solves the diverse heterogeneity problems by mapping MetaData Registry (MDR) based on ISO/IEC 11179 and Schema Repository (SCR).

• The KIPS Transactions:PartD
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• v.11D no.4
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• pp.783-798
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• 2004

An e-business client application in ubiquitous mobile computing environment may become disconnected from the enterprise server due to broken communication connections caused by the limitation of mobile computing environments(limited battery life of the mobile device, low bandwidth communication, incomplete wireless communication infrastructure, etc). It Is even Possible that mobile client application Intentionally operates in disconnected mode to reduce communication cost and the power consumption of the mobile device. We use “data hoarding” as a means of providing local autonomy to allow transactions to be processed and committed on the mobile host despite of disconnection. The key problem to this approach is the synchronization problem that serialize potentially conflicting updates from disconnected clients on master objects of the server database. In this paper, we present a new transaction synchronizing method that splits a transaction into a set of independent component transactions and give the synchronization priority on each component taking the possibility of use and conflicts in the server into consideration. Synchronization is performed component by component based un synchronization priority. After the Preferred component of a no bile transaction succeeds in synchronization with the server, the mobile transaction can pre-commit at server. A pre-committed transaction's updated value is made visible at server before the final commit of the transaction. The synchronization of the component with low synchronization priority can be delayed in adaption to wireless bandwidth and computing resources. As a result, the availability of important data updated by mobile client is increased and it can maximize the utilization of the limited wireless bandwidth and computing resources.

• Journal of the Korean Association of Geographic Information Studies
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• v.7 no.1
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• pp.84-93
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• 2004

Recently, domain-specific demands with respect to practical applications and analysis scheme using spatial thematic information are increasing. Accordingly, in this study, GIS-based application program is implemented to perform spatial analysis in transportation geography with base road layer data. Using this program, quantitative estimation of circuity and accessibility, which can be extracted from nodes composed of the graph-typed network structure, in a arbitrary analysis zone or administrative boundary zone is possible. Circuity is a concept to represent the difference extent between actual nodes and fully connected nodes in the analysis zone. While, accessibility can be used to find out extent of accessibility or connectivity between all nodes contained in the analysis zone, judging from inter-connecting status of the whole nodes. In put data of this program, which was implemented in AVX executable extension using AvenueTM of ArcView, is not transportation database information based on transportation data model, but layer data, directly obtaining from digital map sets. It is thought that computation of circuity and accessibility can be used as kinds of spatial analysis functions for GIS applications in the transportation field.

• Korean Journal of Remote Sensing
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• v.23 no.4
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• pp.297-309
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• 2007

The first Korean geostationary weather satellite, Communications, Oceanography and Meteorology Satellite (COMS) will be launched in 2008. The ground station for COMS needs to perform geometric correction to improve accuracy of satellite image data and to broadcast geometrically corrected images to users within 30 minutes after image acquisition. For such a requirement, we developed automated and fast geometric correction techniques. For this, we generated control points automatically by matching images against coastline data and by applying a robust estimation called RANSAC. We used GSHHS (Global Self-consistent Hierarchical High-resolution Shoreline) shoreline database to construct 211 landmark chips. We detected clouds within the images and applied matching to cloud-free sub images. When matching visible channels, we selected sub images located in day-time. We tested the algorithm with GOES-9 images. Control points were generated by matching channel 1 and channel 2 images of GOES against the 211 landmark chips. The RANSAC correctly removed outliers from being selected as control points. The accuracy of sensor models established using the automated control points were in the range of $1{\sim}2$ pixels. Geometric correction was performed and the performance was visually inspected by projecting coastline onto the geometrically corrected images. The total processing time for matching, RANSAC and geometric correction was around 4 minutes.

• Journal of the Korean Geotechnical Society
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• v.35 no.6
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• pp.17-26
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• 2019

In this study, the statistical characteristics of the resistance bias factors were analyzed using a high-quality field load test database, and the total resistance bias factors were estimated considering the soil uncertainty and construction errors for the application of the limit state design of aggregate pier foundation. The MLR model by Bong and Kim (2017), which has a higher prediction performance than the previous models was used for estimating the resistance bias factors, and its suitability was evaluated. The chi-square goodness of fit test was performed to estimate the probability distribution of the resistance bias factors, and the normal distribution was found to be most suitable. The total variability in the nominal resistance was estimated including the uncertainty of undrained shear strength and construction errors that can occur during the aggregate pier construction. Finally, the probability distribution of the total resistance bias factors is shown to follow a log-normal distribution. The parameters of the probability distribution according to the coefficient of variation of total resistance bias factors were estimated by Monte Carlo simulation, and their regression equations were proposed for simple application.

• Korean Journal of Remote Sensing
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• v.34 no.6_3
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• pp.1383-1398
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• 2018

Sea surface wind is one of the most fundamental variables for understanding diverse marine phenomena. Although scatterometers have produced global wind field data since the early 1990's, the data has been used limitedly in oceanic applications due to it slow spatial resolution, especially at coastal regions. Synthetic Aperture Radar (SAR) is capable to produce high resolution wind field data. KOMPSAT-5 is the first Korean satellite equipped with X-band SAR instrument and is able to retrieve the sea surface wind. This study presents the validation results of sea surface wind derived from the KOMPSAT-5 backscattering coefficient data for the first time. We collected 18 KOMPSAT-5 ES mode data to produce a matchup database collocated with buoy stations. In order to calculate the accurate wind speed, we preprocessed the SAR data, including land masking, speckle noise reduction, and ship detection, and converted the in-situ wind to 10-m neutral wind as reference wind data using Liu-Katsaros-Businger (LKB) model. The sea surface winds based on XMOD2 show root-mean-square errors of about $2.41-2.74m\;s^{-1}$ depending on backscattering coefficient conversion equations. In-depth analyses on the wind speed errors derived from KOMPSAT-5 backscattering coefficient data reveal the existence of diverse potential error factors such as image quality related to range ambiguity, discrete and discontinuous distribution of incidence angle, change in marine atmospheric environment, impacts on atmospheric gravity waves, ocean wave spectrum, and internal wave.

• Journal of IKEEE
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• v.23 no.1
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• pp.112-119
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• 2019

In this paper, we propose a deep learning structure suitable for embedded system. The flame detection process of the proposed deep learning structure consists of four steps : flame area detection using flame color model, flame image classification using deep learning structure for flame color specialization, $N{\times}N$ cell separation in detected flame area, flame image classification using deep learning structure for flame shape specialization. First, only the color of the flame is extracted from the input image and then labeled to detect the flame area. Second, area of flame detected is the input of a deep learning structure specialized in flame color and is classified as flame image only if the probability of flame class at the output is greater than 75%. Third, divide the detected flame region of the images classified as flame images less than 75% in the preceding section into $N{\times}N$ units. Fourthly, small cells divided into $N{\times}N$ units are inserted into the input of a deep learning structure specialized to the shape of the flame and each cell is judged to be flame proof and classified as flame images if more than 50% of cells are classified as flame images. To verify the effectiveness of the proposed deep learning structure, we experimented with a flame database of ImageNet. Experimental results show that the proposed deep learning structure has an average resource occupancy rate of 29.86% and an 8 second fast flame detection time. The flame detection rate averaged 0.95% lower compared to the existing deep learning structure, but this was the result of light construction of the deep learning structure for application to embedded systems. Therefore, the deep learning structure for flame detection proposed in this paper has been proved suitable for the application of embedded system.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.4
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• pp.577-584
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• 2021

Electrical energy is an essential component in present societies, which is an important basis for our technological society. In the design of new power infrastructure, it is important to consider the psychological aspects of how our culture considers and aspects its development as an integral component of the community environment. The construction of new high voltage overhead transmission lines has become a controversial issue for public policy of government due to social opposition. The members of community are concerned about how these power lines may have an impact on their lives, basically caused by their effects on health and safety. The landscape and visual impact is one of the most impact that can be easily perceived for local community. The computer 3D simulation of new landscape is illustrated by a real life use corresponding to the selection of the power line route with least observability for local community. This paper used ArcGIS(geographic information system tool) for planning, survey, basic route and detailed route, route for implementation of transmission line corridor. Also, the paper showed the map of natural environment, living environment, safety and altitude using database of power line corridor, and transmission siting model was developed by this study. The suggested landscape of computer simulation with lowest visibility on a power line zone can contribute to reducing oppositions of local community and accelerating the construction of new power lines.

• Journal of the Korea Institute of Building Construction
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• v.20 no.6
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• pp.505-514
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• 2020

This research introduces the method of developing Korea BIM standard (KBIMS) architectural and structural element library and the methodology of converting KBIMS IFC property names with special characters. Diverse BIM tools are utilizing in project, however BIM library researches lack diversity on BIM tool selection. This research described the method to generate twelve categories and seven hundred and ninety-three elements library containing geometrical and numerical data in CATIA V6. KBIMS has its special property data naming systems which was the challenge inputting to ENOVIA IFC database. Three mapping methods for special naming characters had been developed and the ASCII code method was applied. In addition, the convertor prototype had been developed for searching and replacing the ASCII codes into the original KBIMS IFC property names. The methodology was verified by exporting 2,443 entities without data loss in the sample model conversion test. This research would provide a wider choice of BIM tool selection for applying KBIMS. Furthermore, the research would help on the reduction of data interoperability issues in projects. The developed library would be open to the public, however the continuous update and maintenance would be necessary.